mlsanityData to 7 Oct 2026

Combining Deep Learning with Good Old-Fashioned Machine Learning

arXiv 2207.03757 ↗First posted 8 Jul 2022cs.LG cs.CVcited by 2

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Abstract (arXiv)

We present a comprehensive, stacking-based framework for combining deep learning with good old-fashioned machine learning, called Deep GOld. Our framework involves ensemble selection from 51 retrained pretrained deep networks as first-level models, and 10 machine-learning algorithms as second-level models. Enabled by today's state-of-the-art software tools and hardware platforms, Deep GOld delivers consistent improvement when tested on four image-classification datasets: Fashion MNIST, CIFAR10, CIFAR100, and Tiny ImageNet. Of 120 experiments, in all but 10 Deep GOld improved the original networks' performance.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 5 of its 29 references that are in the map. First posted on arXiv 8 Jul 2022.

Builds on

5 of 29 references.

References · 5

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,120
  3. 2019Optuna: A Next-generation Hyperparameter Optimization Frameworkcited by 2,455
  4. 2021Tabular Data: Deep Learning is Not All You Needcited by 530
  5. 2022Neural Networks with A La Carte Selection of Activation Functionscited by 4

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Citing papers per year: 2023: 2.

2 papers.